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AlpineDataWorks Intelligence Server

Regulatory-Activity Index

adw.adw_127
Read-only

Returns a 0-100 federal regulatory-activity index (composite z-score of Federal Register rule/notice volume and trend, weekly, 31-year history) with score, trend, and pinned methodology_version. Call when the user asks about federal rulemaking pace, regulation volume, Federal Register activity, agency rules, or compliance workload, or when timing regulatory-change monitoring, compliance-impact briefs, or alert gating on rising rulemaking. Updates: weekly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoOptional: return a daily HISTORY series of the last N days (up to 5 years of real archived data) instead of the current snapshot. History requires Gold tier; without it, the current snapshot is returned.

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only and closed-world, and the description adds meaningful context: the index includes score, trend, and pinned methodology_version, is weekly, and has a 31-year history. This goes beyond the annotation by clarifying what the returned data contains and its update cadence.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact yet informative, with the main return value front-loaded, followed by usage triggers and update frequency. Every sentence contributes value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only tool with one optional parameter fully described in the schema, the description covers the essential aspects: what is returned (score, trend, methodology_version), when to use it, and how often it updates. No output schema exists, but the enum of returned components is stated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema fully documents the single optional 'days' parameter (100% coverage), so the baseline is 3. The description adds no additional parameter semantics beyond what the schema already states about returning a history series instead of the current snapshot.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Returns') and clearly identifies the resource: a 0-100 federal regulatory-activity index based on Federal Register volume and trend, with 31-year weekly history. It is highly specific and distinguishable from the many sibling tools, even without naming an alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit 'Call when' list covering relevant user intents (rulemaking pace, regulation volume, Federal Register activity) and use cases (monitoring, compliance briefs, alert gating). However, it does not include when-not scenarios or name alternative tools, so it does not fully meet the 5-level criterion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation1/5

With 318 tools named adw.adw_###, agents cannot tell them apart without reading full descriptions. Multiple tools cover the same domain (e.g., at least three USD strength scores: adw_055, adw_250, adw_580; four supply-chain stress scores: adw_009, adw_019, adw_020, adw_547), making misselection highly likely.

Naming Consistency3/5

The vast majority follow a consistent numeric ID pattern (adw.adw_###), but a small set breaks this with descriptive snake_case names (adw.catalog, adw.sample, adw.county_cancer, etc.). The numeric IDs are predictable but convey no semantic meaning, mixing with the few named tools and creating moderate inconsistency.

Tool Count1/5

318 tools is far beyond any reasonable scope for an intelligence server; even the largest sophisticated APIs rarely exceed 50. This extreme count suggests poor curation and will overwhelm agents with choice, making efficient tool selection impractical.

Completeness3/5

The server covers an extremely broad range of domains (crypto, macro, supply chain, healthcare, climate, county demographics), and includes discovery tools like adw.catalog and adw.sample. However, the surface is redundant and not systematically complete—many overlapping indices exist while other potentially valuable operations (e.g., raw data export, historical trend queries) are missing, leaving moderate gaps.

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